期刊论文详细信息
BMC Bioinformatics
Reference-free deconvolution of DNA methylation data and mediation by cell composition effects
Methodology Article
Carmen J. Marsit1  David C. Christiani2  Karl T. Kelsey3  Tan A. Ince4  Molly L. Kile5  E. Andres Houseman5 
[1] Department of Community and Family Medicine, Dartmouth Medical School, Hanover, NH, USA;Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA;Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University, Providence, USA;Department of Pathology, University of Miami, Miller School of Medicine, Miami, FL, USA;School of Biological and Population Health Sciences, College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA;
关键词: Deconvolution;    DNA methylation;    Epigenetics;    Non-negative matrix factorization;   
DOI  :  10.1186/s12859-016-1140-4
 received in 2016-04-04, accepted in 2016-06-19,  发布年份 2016
来源: Springer
PDF
【 摘 要 】

BackgroundRecent interest in reference-free deconvolution of DNA methylation data has led to several supervised methods, but these methods do not easily permit the interpretation of underlying cell types.ResultsWe propose a simple method for reference-free deconvolution that provides both proportions of putative cell types defined by their underlying methylomes, the number of these constituent cell types, as well as a method for evaluating the extent to which the underlying methylomes reflect specific types of cells. We demonstrate these methods in an analysis of 23 Infinium data sets from 13 distinct data collection efforts; these empirical evaluations show that our algorithm can reasonably estimate the number of constituent types, return cell proportion estimates that demonstrate anticipated associations with underlying phenotypic data; and methylomes that reflect the underlying biology of constituent cell types.ConclusionsOur methodology permits an explicit quantitation of the mediation of phenotypic associations with DNA methylation by cell composition effects. Although more work is needed to investigate functional information related to estimated methylomes, our proposed method provides a novel and useful foundation for conducting DNA methylation studies on heterogeneous tissues lacking reference data.

【 授权许可】

CC BY   
© The Author(s). 2016

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